Objective: Quantify the effect of thermal stressors on human performance. Background: Most reviews of the effect of environmental stressors on human performance are qualitative. A quantitative review provides a stronger aid in advancing theory and practice. Method: Meta-analytic methods were applied to the available literature on thermal stressors and performance. A total of 291 references were collected. Forty-nine publications met the selection criteria, providing 528 effect sizes for analysis. Results: Analyses confirmed a substantial negative effect on performance associated with thermal stressors. The overall effect size for heat was comparable to that for cold. Cognitive performance was least affected by thermal stressors, whereas both psychomotor and perceptual task performance were degraded to a greater degree. Other variables were identified that moderated thermal effects. Conclusion: Results confirmed the importance of task type, exposure duration, and stressor intensity as key variables impacting how thermal conditions affect performance. Results were consistent with the theory that stress forces the individual to allocate attentional resources to appraise and cope with the threat, which reduces the capacity to process task-relevant information. This represents a maladaptive extension of the narrowing strategy, which acts to maintain stable levels of response when stress is first encountered. Application: These quantitative estimates can be used to design thermal tolerance limits for different task types. Although results indicate the necessity for further research on a variety of potentially influential factors such as acclimatization, the current summary provides effect size estimates that should be useful in respect to protecting individuals exposed to adverse thermal conditions.
AbstractIntroductionIn order to end the tuberculosis (TB) epidemic by 2035, countries must achieve a 10% annual decline in tuberculosis incidence rates by 2025. Provision of antiretroviral therapy (ART) has been associated with population level decreases in TB notification rates. We aimed to assess whether the progressive scale‐up of ART provision over the past nine years has had an effect on population level trends of TB notification in Uganda stratified by sex and HIV status.MethodsThe study area consisted of Kampala and eight surrounding districts. Annual TB notifications and mid‐year populations were used to calculate notification rates per 100,000 population from the study area. Numbers alive and retained on ART were used to calculate ART coverage, overall and by sex. TB notification rates (TBNRs) overall and stratified by sex and HIV status were calculated for the period 2009 to 2017. Trends in TBNRs before and after rollout of universal ART for pregnant women in 2013 were examined using Poisson regression models. To gain insight into the trends in CD4+ T‐cell counts at ART initiation over the study period, we performed a sub analysis of patient level data from the Infectious Diseases Institute clinic.ResultsFrom 2009 to 2017, ART coverage increased by 27.6% among men and by 35.4% among women. TBNRs declined during the same period. Overall, the average annual percentage decline in TBNRs was −3.5% (95%CI −3.7% to −3.3%), (−2.3% (95%CI −2.6% to −1.9%) in men and −5.4% (95%CI −5.7% to −5.0%) in women). ART coverage increased after 2013 but this was not associated with an accelerated decline in overall TBNRs among HIV‐positive persons −3.6% before 2013 and −5.2% after 2013; p = 0.33. The proportion of patients initiating ART with CD4+ T‐cell count ≤ 200 cells/mL did not decrease significantly after 2013 (42.2% to 32.2%, p = 0.05).ConclusionsAlthough ART scale‐up was temporally associated with a decline in TB notification rates, the achieved rates of decline are below those required to achieve the End TB Targets. Additional investments in tuberculosis control should include efforts to promote earlier care seeking and ART initiation among HIV‐positive persons.
IntroductionHepatitis C virus (HCV) and HIV infection frequently co‐occur due to shared transmission routes. Co‐infection is associated with higher HCV viral load (VL), but less is known about the effect of HCV infection on HIV VL and risk of onward transmission.MethodsWe undertook a systematic review comparing 1) HIV VL among ART‐naïve, HCV co‐infected individuals versus HIV mono‐infected individuals and 2) HIV VL among treated versus untreated HCV co‐infected individuals. We performed a random‐effects meta‐analysis and quantified heterogeneity using the I2 statistic. We followed Cochrane Collaboration guidelines in conducting our review and PRISMA guidelines in reporting results.Results and discussionWe screened 3925 articles and identified 17 relevant publications. A meta‐analysis found no evidence of increased HIV VL associated with HCV co‐infection or between HIV VL and HCV treatment with pegylated interferon‐alpha‐2a/b and ribavirin.ConclusionsThis finding is in contrast to the substantial increases in HIV VL observed with several other systemic infections. It presents opportunities to elucidate the biological pathways that underpin epidemiological synergy in HIV co‐infections and may enable prediction of which co‐infections are most important to epidemic control.
AbstractIntroduction: Achieving the UNAIDS goals of 90–90‐90 will require more than doubling the number of people accessing HIV care in Uganda. Community‐based programmes for entry into HIV care are effective strategies to expand access to HIV care, but few programmes have been evaluated with a particular focus on scale‐up.Methods: Integrated Community Based Initiatives, a Uganda‐based non‐governmental organization, designed and implemented a programme of community‐based HIV counselling and testing and facilitated linkage to care utilizing community health extension workers (CHEWs) in rural Sheema District, Uganda. CHEWs performed programme activities during 1 October 2015 through 31 March 2016. Outcomes for this evaluation were (1) the number of people tested for HIV, and (2) the proportion of those testing positive who were seen at an ART clinic within three months of their positive test, and (3) the cost of the programme per person newly diagnosed with HIV. Microcosting methods were used to calculate the programme costs. Program scalability factors were evaluated using a published framework.Results: Sixty‐two CHEWs attended a five‐day training that introduced the biology of HIV, the conduct of confidential HIV testing, HIV prevention messages, and linkage, referral, and reporting requirements. CHEWs received a $30 monthly stipend and a field testing kit that included a bicycle, field bag, umbrella, gumboots, reporting booklet, pens, and HIV testing materials. Trained CHEWs tested 43,696 persons for HIV infection during the six‐month programme period. Nine‐hundred seventy‐four participants (2.2%) were identified as HIV positive, and 623 participants (64%) were linked to HIV care. An estimated 69% of adult residents received testing as part of this campaign. The programme cost $3.02 per person test, $135.70 per positive person identified, and $212.15 per HIV‐positive person linked to care.Conclusions: Lay community health extension workers (CHEWs) can be rapidly trained to scale‐up home‐based HIV testing and counselling (HTC) and linkage to care in a high‐quality and low‐cost manner to large numbers of people in a rural, high burden setting. A combination HIV testing approach, such as adding partner testing to community‐based testing, could increase the proportion of HIV‐positive persons identified.
INTRODUCTION: Understanding how to deliver interventions more effectively is a growing emphasis in Global Health. Simultaneously, health system strengthening is a key component to improving delivery. As a result, it is challenging to evaluate programme implementation while reflecting real-world complexity. We present our experience in using a health systems modelling approach as part of a mixed-methods evaluation and describe applications of these models. METHODS: We developed a framework for how health systems translate financial inputs into health outcomes, with in-country and international experts. We collated available data to measure framework indicators and developed models for malaria in Democratic Republic of the Congo (DRC), and tuberculosis in Guatemala and Senegal using Bayesian structural equation modelling. We conducted several postmodelling analyses: measuring efficiency, assessing bottlenecks, understanding mediation, analysing the cascade of care and measuring subnational effectiveness. RESULTS: The DRC model indicated a strong relationship between shipment of commodities and utilisation thereof. In Guatemala, the strongest model coefficients were more evenly distributed. Results in Senegal varied most, but pathways related to community care had the strongest relationships. In DRC, we used model results to estimate the end-to-end cost of delivering commodities. In Guatemala, we used model results to identify potential bottlenecks and understand mediation. In Senegal, we used model results to identify potential weak links in the cascade of care, and explore subnationally. CONCLUSION: This study demonstrates a complementary modelling approach to traditional evaluation methods. Although these models have limitations, they can be applied in a variety of ways to gain greater insight into implementation and functioning of health service delivery.
High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations
High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations